CN114971412A - Order distribution method, order distribution platform, order distribution system and storage medium - Google Patents

Abstract

The invention discloses an order distribution method, an order distribution platform, an order distribution system and a storage medium. The method includes: receiving order information uploaded by a user through a terminal, where the order information includes user level and reservation address information; obtaining the levels of all salesmen information, and filter out the first salesperson set whose level information matches the user level; obtain the real-time location information of each salesperson in the first salesperson set, and filter out the first salesperson set whose real-time location information matches the reservation address information. Second salesperson set; prioritize all salespersons in the second salesperson set based on preset rules; assign the order information to the task list of the target salesperson, where the target salesperson is the one with the highest priority Salesperson to ensure that orders can be processed in a timely manner. Such an order distribution scheme increases the diversity of order distribution methods, has a high degree of flexibility, and provides a better user experience.

Description

Order distribution method, order distribution platform, order distribution system and storage medium

technical field

The present invention relates to the field of computer technology, in particular to an order distribution method, an order distribution platform, an order distribution system and a storage medium.

Background technique

With the development of computer technology, various financial services of banks can be handled through computers, such as account opening, transfer, credit card processing, financial transactions and other services. When a bank clerk is required to go to the door to handle the business, the current distribution method of the business order is usually to send the order to the clerk whose real-time location information is consistent with the order reservation address information. When there are a lot of orders from the salesperson whose real-time location information is consistent with the order reservation address information, if multiple newly received orders are given to the salesperson for processing, the salesperson may not be able to handle it, which will affect the order. processing speed. It can be seen that the existing order allocation method is too simple and not flexible enough.

SUMMARY OF THE INVENTION

The purpose of this application is to provide an order distribution method, an order distribution platform, an order distribution system and a storage medium, so as to solve the problem that the order distribution method in the prior art is too simple and not flexible enough.

A first aspect of the embodiments of the present application provides an order allocation method, including:

Receive order information uploaded by the user through the terminal, where the order information includes user level and reservation address information;

Obtain the level information of all the salespersons, and filter out the first salesperson set whose level information matches the user level;

Obtain the real-time location information of each salesperson in the first salesperson set, and filter out the second salesperson set whose real-time location information matches the reservation address information from the first salesperson set;

Prioritize all salespersons in the second salesperson set based on preset rules;

The order information is allocated to the task list of the target salesperson, where the target salesperson is the salesperson with the highest priority.

In one embodiment, the obtaining of the level information of all salespersons includes:

Obtain the business information of the salesman;

According to the business information, a corresponding business type is determined, and the business type is input into a preset salesperson matching model for matching, so as to obtain level information matching the business information.

In one embodiment, the filtering out the second salesperson set whose real-time location information matches the reservation address information from the first salesperson set includes:

The urban area is divided into grids according to the population density distribution, and multiple grid areas are obtained;

Taking the grid area where the reservation address information is located as the center, if the real-time location information is within 8 grid areas surrounding the center, the real-time location information matches the reservation address information, wherein, The grid area in the center and the 8 grid areas around the center are distributed in a nine-square grid.

In one embodiment, the filtering out the second salesperson set whose real-time location information matches the reservation address information from the first salesperson set includes:

Draw a heat map based on the historical order location information of the target city area;

The heat map is divided into grids according to a preset ratio strategy to obtain a plurality of grid regions;

Taking the grid area where the reservation address information is located as the center, if the real-time location information is within 8 grid areas surrounding the center, the real-time location information matches the reservation address information, wherein, The grid area in the center and the 8 grid areas around the center are distributed in a nine-square grid.

In one embodiment, the filtering out the second salesperson set whose real-time location information matches the reservation address information from the first salesperson set includes:

If the path distance between the real-time location information and the reservation address information is less than or equal to a preset distance, the real-time location information matches the reservation address information.

In one embodiment, described based on preset rules, all salespersons in the second salesperson set are prioritized, including,

Regularly acquire all business data within the most recent preset time range, input the acquired business data into the preset data statistical analysis system for statistical analysis, and obtain the value of each preset performance index of each salesperson through statistical analysis;

Calculate the value of each preset performance index of each salesperson according to the preset scoring calculation rules, and calculate the total performance score of each salesperson;

Prioritize each salesperson in descending order of their total performance points.

A second aspect of the embodiments of the present application provides an order distribution platform, including:

a receiving module, configured to receive order information uploaded by the user through the terminal, where the order information includes user level and reservation address information;

The first screening module is used to obtain the level information of all salesmen, and filter out the first salesperson set whose level information matches the user level;

The second screening module is configured to obtain the real-time location information of each salesperson in the first salesperson set, and filter out the second salesperson whose real-time location information matches the reservation address information from the first salesperson set gather;

A priority sorting module, used for prioritizing all salespersons in the second salesperson set based on preset rules;

The allocation module is used for allocating the order information to the task list of the target salesperson, wherein the target salesperson is the salesperson with the highest priority.

A second aspect of the embodiments of the present application provides an order distribution platform, including:

a receiving module, configured to receive multiple order information uploaded by multiple users through the terminal, wherein the order information includes reservation address information;

an area determination module, configured to determine a target area and an adjacent area according to the reservation address information and a preset area division rule;

The determining module is used to obtain the real-time position information corresponding to each salesman, and determine the list of the first salesperson whose real-time position information is located in the target area and the second list whose real-time position information is located in the adjacent area. salesman list;

a collection module, used to collect the current number of unfinished orders of each salesperson in the first salesperson list;

a judging module for judging whether the current number of unfinished orders of all salespersons in the first salesperson list is greater than the preset number of unfinished orders;

The allocation module is used to allocate multiple order information to the task list of the target salesperson when the current number of unfinished orders of all salespersons in the first salesperson list is greater than the preset number of unfinished orders, wherein, The target salespersons are several salespersons in the second salesperson list whose current number of unfinished orders is less than the preset number of unfinished orders.

A third aspect of the embodiments of the present application provides an order distribution platform, including a memory, a processor, and a computer program stored in the memory and executable on a computer device, the processor implements the computer program when the processor executes the computer program Steps of the order distribution method provided by the first solution.

A fourth aspect of the embodiments of the present application provides an order distribution system, which includes several clients, servers, and the aforementioned order distribution platform; the several clients and servers are all connected in communication with the platform.

A fifth aspect of the embodiments of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, implements each of the order distribution methods provided in the first solution. step.

Implementing an order distribution method, an order distribution platform, an order distribution system, and a storage medium provided by the embodiments of the present application has the following beneficial effects:

An order distribution method, an order distribution platform, an order distribution system and a storage medium provided by the embodiments of the present application, by receiving order information uploaded by a user through a terminal, the order information includes user level and reservation address information; level information, and filter out the first salesperson set whose level information matches the user level; obtain the real-time location information of each salesperson in the first salesperson set, and filter out the first salesperson set from the first salesperson set A second salesperson set whose real-time location information matches the reservation address information; all salespersons in the second salesperson set are prioritized based on preset rules; the order information is allocated to the target salesperson's In the task list, the target salesperson is the salesperson with the highest priority to ensure that the order can be processed in time. Such an order distribution scheme increases the diversity of order distribution methods, has a high degree of flexibility, and provides a better user experience.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for the present invention. In some embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

FIG. 1 is a first implementation flowchart of an order allocation method provided by an embodiment of the present invention;

Fig. 2 is the second realization flow chart of the order distribution method provided by the embodiment of the present invention;

Fig. 3 is the third realization flow chart of the order distribution method provided by the embodiment of the present invention;

Fig. 4 is the first flow chart of step S20 in Fig. 1;

Fig. 5 is the second flow chart of step S20 in Fig. 1;

6 is a schematic diagram of functional modules of an order distribution platform provided by an embodiment of the present invention;

7 is a schematic diagram of a hardware structure of an order distribution platform provided by an embodiment of the present invention;

FIG. 8 is a schematic diagram of a hardware structure of an order distribution system of an order distribution platform provided by an embodiment of the present invention.

Detailed ways

In order to make the technical problems, technical solutions and beneficial effects to be solved by the present application clearer, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

An order allocation method provided by an embodiment of the present application is applied to a computer device. During implementation, the order distribution method is configured on a computer device in the form of a target script, and the computer device executes the various steps of the order distribution method provided in this embodiment by executing the target script. The execution body is the target server in the server cluster for allocating the order. Here, the server cluster may be a server cluster composed of multiple servers, and a distributed order distribution system is constructed based on the server cluster, so that each component required for constructing the distributed order distribution system can be configured in each server in the server cluster, A server configured with components of a distributed order distribution system may also be referred to as a component server. Data sharing or data synchronization can be performed among the servers in the server cluster. On this basis, a target script file is configured to any server in the server cluster, and the target script file describes the order distribution method provided in this embodiment, so that the server configured with the target script file can execute the target script file by executing the target script file. , and then perform the various steps in the order allocation method. Alternatively, by configuring a new server for the server cluster, a target script file is configured on the new server, and the target script file describes the order distribution method provided by this embodiment, so that the new server can execute the target script file, and then Perform the various steps in order allocation.

During implementation, the target server in the server cluster for allocating orders receives order information uploaded by the user through the terminal, where the order information includes user level and reservation address information. Obtain the level information of all the salespersons, and filter out the first salesperson set whose level information matches the user level. Obtain the real-time location information of each salesperson in the first salesperson set, and filter out a second salesperson set whose real-time location information matches the reservation address information from the first salesperson set. All salespersons in the second salesperson set are prioritized based on preset rules. The order information is allocated to the task list of the target salesperson, wherein the target salesperson is the salesperson with the highest priority, so as to ensure that the order can be processed in time. Such an order distribution scheme increases the diversity of order distribution methods, has a high degree of flexibility, and provides a better user experience.

Referring to FIG. 1 , FIG. 1 shows a first implementation flow chart of the order allocation method provided by the embodiment of the present application. This order allocation method includes:

S10: Receive order information uploaded by the user through the terminal, where the order information includes user level and reservation address information.

In step S10, the order information is contained in the electronic order that the user needs to request the insurance institution to assign a salesman to handle the business at the door, and sends a business processing request through the insurance institution APP or the client of the insurance institution, and the salesperson handles the business for the user. order information. The order information includes the user's name, gender, age, mobile phone number, business type handled, user level, reservation address information, etc. The user fills in the information on the electronic order and uploads the order information on the client, and the server receives the order information uploaded by the user.

S20: Acquire the level information of all salespersons, and filter out a first salesperson set whose level information matches the user level.

S30: Acquire real-time location information of each salesperson in the first salesperson set, and filter out a second salesperson set whose real-time location information matches the reservation address information from the first salesperson set.

In step S30, acquiring the real-time location information of each salesman may be satellite positioning information uploaded by the salesman on the order distribution system in real time, or may be input by voice or manually fill in the real-time location information for the salesman. In addition, obtaining the real-time location information corresponding to each salesperson in the salesperson information set may also be based on the first location information of the electronic order currently being processed by each salesperson, and/or the second location of the next electronic order to be processed information is jointly determined.

The user submits the reservation address information through the terminal, and the real-time location information of the salesman also needs to be collected on the order distribution system, and the server compares the acquired real-time location information with the reservation address information. To compare the real-time location information of the salesman with the reservation address information, it is necessary to specify the smallest unit, such as a certain street. If the real-time location information matches the reservation address information, at this time, the salesperson information is included in the first salesperson list.

When the GPS positioning information uploaded by the salesperson cannot be used to determine the real-time location information of each salesperson, or when the GPS positioning information uploaded by the salesperson is not received, it can be based on the first location information of the electronic order currently being processed by each salesperson, and/or the second location information of the next electronic order to be processed jointly determine the real-time location information of each salesperson. When the network status is not good, it becomes difficult to upload GPS positioning information, and according to the reservation address information of the clerk's processing and pending electronic orders that have been determined on the order distribution system, for example, there is a clerk in the clerk's task list. Processed and pending order information, because the clerk processes the order information according to the order of the order information in the task list, the real-time location information of the clerk may be the address on the order being processed, or the address below The address of a pending order message, more likely a path between the order being processed and the address of the next pending order. Therefore, the real-time location information corresponding to each salesperson can be determined based on the electronic first location information being processed by each salesperson and/or the second location information of the next electronic order to be processed.

S40: Prioritize all the salespersons in the second salesperson set based on a preset rule.

S50: Allocate the order information to the task list of the target salesperson, where the target salesperson is the salesperson with the highest priority.

Referring to FIG. 2 , FIG. 2 shows a second implementation flowchart of the order allocation method provided by the embodiment of the present application. This order allocation method includes:

S10: Receive order information uploaded by the user through the terminal, where the order information includes user level and reservation address information.

S21: Obtain the business information of the salesperson.

In step S21, the business information includes customer information, historical policy transaction records, appointment time, appointment location, and the like.

S22: Determine a corresponding service type according to the service information, input the service type into a preset salesman matching model for matching, and obtain grade information matching the service information.

In step S22, the tag set of the current salesperson's docking with customers and purchased products is extracted from the business information, the business type corresponding to the business information is determined by the tag set, and the current salesperson is matched by inputting the business type into the preset salesperson matching model. Required salesperson level. For example, the current business information has labels such as customer gender: female, 23 years old, car insurance, high family income, and per capita number of insurance purchases by a family of 1.8. If the current business information obtained through these labels is rated as A, the historical business display is connected to this category. The required level of the customer's salesperson needs to be between a-b, and the preliminary screening level is the salesperson between a-b

S23: Filter out the first salesman set whose level information matches the user level.

In step S23, the salespersons whose level information matches the user level are screened out to obtain a first salesperson set.

S30: Acquire real-time location information of each salesperson in the first salesperson set, and filter out a second salesperson set whose real-time location information matches the reservation address information from the first salesperson set.

S40: Prioritize all the salespersons in the second salesperson set based on a preset rule.

S50: Allocate the order information to the task list of the target salesperson, where the target salesperson is the salesperson with the highest priority.

Referring to FIG. 3 , FIG. 3 shows a third implementation flowchart of the order allocation method provided by the embodiment of the present application. This order allocation method includes:

S10: Receive order information uploaded by the user through the terminal, where the order information includes user level and reservation address information.

S21: Obtain the business information of the salesperson.

S22: Determine a corresponding service type according to the service information, input the service type into a preset salesman matching model for matching, and obtain grade information matching the service information.

S23: Filter out the first salesman set whose level information matches the user level.

S30: Acquire real-time location information of each salesperson in the first salesperson set, and filter out a second salesperson set whose real-time location information matches the reservation address information from the first salesperson set.

S41 : Acquire all business data within the most recent preset time range regularly, input the acquired business data into a preset data statistical analysis system for statistical analysis, and obtain the value of each preset performance index of each salesperson through statistical analysis .

In step S41, regularly acquire all business data within the most recent preset time range (for example, within the last month), and the business data includes business handling records (including new insurance handling records, renewal handling records), expired service information, etc. Each business data contains information such as the salesperson's name or number, business amount and so on. The electronic device has a pre-set data statistical analysis system, and the electronic device inputs all the acquired business data into the data statistical analysis system. business data, and then perform statistics and calculation of each preset performance index on the business data associated with each salesperson, so as to obtain the value of each preset performance index for each salesperson, and the preset performance indicators include Policy premiums, renewal rates, activity rates, etc.

S42: Calculate the obtained value of each preset performance index of each salesperson according to the preset scoring calculation rule, and calculate the total performance score of each salesperson.

The preset scoring calculation rule may be a weighted summation of the values of each preset performance indicator according to preset weights.

S43: Prioritize each salesperson in descending order of the total performance score.

S50: Allocate the order information to the task list of the target salesperson, where the target salesperson is the salesperson with the highest priority.

In one embodiment, as shown in FIG. 4 , the step S30 specifically includes the following steps:

S31: Perform grid division on the urban area according to the population density distribution to obtain a plurality of grid areas.

Specifically, grid division is based on the large-scale data of the target urban area, and according to the population density distribution in the target urban area, it is divided into different grid cells by horizontal aggregation or vertical decomposition in a certain proportion in space. Because densely populated areas have correspondingly more orders to be processed, it is necessary to divide the target city area into grid divisions, so that the salesmen can centrally process the grid division orders. Divide the target urban area. The target urban area here is not limited to the size range. The urban area is divided according to the needs and specific conditions, but the urban area is generally divided by city. Because the population distribution in the urban area is usually uneven, the urban area is divided into a proportional grid according to the population density distribution in the urban area, and the grid division is obtained by meshing the target urban area.

S32: Taking the grid area where the reservation address information is located as the center, if the real-time location information is within 8 grid areas surrounding the center, the real-time location information matches the reservation address information, Wherein, the grid area in the center and the 8 grid areas surrounding the center are distributed in a nine-square grid.

In one embodiment, as shown in FIG. 5 , the step S30 specifically includes the following steps:

S33: Draw a heat map according to the historical order location information of the target city area.

S34: Perform grid division on the heat map according to a preset scale strategy to obtain a plurality of grid regions.

Specifically, the heat map is the visual data of the area. The heat map is drawn according to the distribution of the historical order location information of the target city area in the target city area, that is, the historical order location density is generated and rendered according to the latitude and longitude corresponding to the historical order location and the map of the target city area. heatmap. Finally, in order to obtain the gridded address division area, the heat map needs to be gridded. According to the preset ratio strategy, the grids with a high density of historical orders in the heat map, that is, the locations with darker colors, are divided into smaller proportions, and the grids with a small density of historical orders in the heat map are divided into grids with a larger proportion. . The grid division not only divides the target city area according to the historical order location information, but also obtains the grid address division area according to the density division of the historical order location. The historical order location information can represent the population density distribution, and the corresponding salespersons and salesperson information sets are configured for each gridded address division area are roughly equal, so that the salespersons in each gridded address division area handle each network. The number of orders in the gridded address division area is more balanced, and there will be no situation where the work of different salesmen is under-saturated or over-saturated.

S35: Taking the grid area where the reservation address information is located as the center, if the real-time location information is within 8 grid areas surrounding the center, the real-time location information matches the reservation address information, Wherein, the grid area in the center and the 8 grid areas surrounding the center are distributed in a nine-square grid.

In one embodiment, the step S30 specifically includes the following steps:

S36: If the path distance between the real-time location information and the reservation address information is less than or equal to a preset distance, the real-time location information matches the reservation address information.

Wherein, the preset distance may be 5-10km.

Based on the above method embodiments, the embodiments of the present invention further provide an order distribution platform. As shown in FIG. 6 , the platform 10 may include the following modules:

The receiving module 11 is used for receiving the order information uploaded by the user through the terminal, the order information includes the user level and the reservation address information;

The first screening module 12 is used to obtain the grade information of all salesmen, and filter out the first salesperson set whose grade information matches the user grade;

The second screening module 13 is configured to obtain the real-time location information of each salesperson in the first salesperson set, and filter out the second service whose real-time location information matches the reservation address information from the first salesperson set collection of members;

A priority sorting module 14, configured to prioritize all salespersons in the second salesperson set based on preset rules;

The allocation module 15 is configured to allocate the order information to the task list of the target salesperson, where the target salesperson is the salesperson with the highest priority.

It should be understood that, in the schematic diagram of the functional modules of the order distribution platform shown in FIG. 6 , each module is used to execute each step in the embodiment corresponding to FIG. The steps have been explained in detail in the above-mentioned embodiments. For details, please refer to the relevant descriptions in the embodiments corresponding to FIGS. 1-5 , which will not be repeated here.

Another embodiment of the present invention provides an order distribution platform. As shown in FIG. 7 , the order distribution platform 10 includes:

One or more processors 110 and the memory 120 are described by taking one processor 110 as an example in FIG. 7 . The processor 110 and the memory 120 may be connected by a bus or in other ways. In FIG. 7 , the connection by a bus is used as an example.

The processor 110 is used to complete various control logics of the platform 10, which can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a single-chip microcomputer, an ARM (Acorn RISCMachine) or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination of these components. Also, the processor 110 may be any conventional processor, microprocessor or state machine. The processor 110 may also be implemented as a combination of computing devices, eg, a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in combination with a DSP, and/or any other such configuration.

The memory 120, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs and modules, such as corresponding program instructions for order allocation in the embodiment of the present invention . The processor 110 executes various functional applications and data processing of the platform 10 by running the non-volatile software programs, instructions and units stored in the memory 120, ie, implements the order allocation method in the above method embodiments.

The memory 120 may include a stored program area and a stored data area, wherein the stored program area may store an operating platform and an application program required for at least one function. The storage data area may store data or the like created according to the use of the platform 10 . Additionally, memory 120 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 120 may optionally include memory located remotely from processor 110, which may be connected to platform 10 through a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

One or more units are stored in the memory 120, and when executed by one or more processors 110, execute the order allocation method in any of the above method embodiments, for example, execute the above-described method step S100 to step S100 in FIG. 1 . S400.

Another embodiment of the present invention further provides an order distribution system. As shown in FIG. 8 , the system includes several clients 20 , a server 30 and the above-mentioned order distribution platform 10 . The several clients 20 and the server 30 are all connected in communication with the order distribution platform 10, wherein the several clients 20 are used for each handler to log in to the order distribution platform 10 and fill in the announcement information acquisition request, and the server 30 is used for storage. official news.

Embodiments of the present invention provide a non-volatile computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are executed by one or more processors, for example, to execute the above-described Method steps in Figures 1-5.

As examples, non-volatile storage media can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) as external cache memory. By way of illustration and not limitation, RAM may be configured in a variety of formats such as Synchronous RAM (SRAM), Dynamic RAM, (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus (Lambas) RAM (DRRAM) and many other forms. The disclosed memory components or memories of the operating environments described herein are intended to include one or more of these and/or any other suitable types of memory.

Of course, those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing relevant hardware (such as processors, controllers, etc.) through a computer program, and the computer program can be stored in In a non-volatile computer-readable storage medium, the computer program may include the processes of the above-mentioned method embodiments when executed. The storage medium may be a memory, a magnetic disk, a floppy disk, a flash memory, an optical memory, and the like.

It should be understood that the above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions described in the foregoing embodiments can still be modified, or some technical features thereof can be equivalently replaced. However, these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included within the protection scope of the present invention.

Claims (10)

1. an order allocation method, is characterized in that, comprises: Receive order information uploaded by the user through the terminal, where the order information includes user level and reservation address information; Obtain the level information of all the salespersons, and filter out the first salesperson set whose level information matches the user level; Obtain the real-time location information of each salesperson in the first salesperson set, and filter out the second salesperson set whose real-time location information matches the reservation address information from the first salesperson set; Prioritize all salespersons in the second salesperson set based on preset rules; The order information is allocated to the task list of the target salesperson, where the target salesperson is the salesperson with the highest priority. 2. method according to claim 1, is characterized in that, described obtaining the grade information of all salesmen, comprises: Obtain the business information of the salesman; According to the business information, a corresponding business type is determined, and the business type is input into a preset salesperson matching model for matching, so as to obtain level information matching the business information. 3. method according to claim 1, is characterized in that, described screening out the second clerk set that described real-time location information matches with described reservation address information from described first clerk set, comprising: The urban area is divided into grids according to the population density distribution, and multiple grid areas are obtained; Taking the grid area where the reservation address information is located as the center, if the real-time location information is within 8 grid areas surrounding the center, the real-time location information matches the reservation address information, wherein, The grid area in the center and the 8 grid areas around the center are distributed in a nine-square grid. 4. method according to claim 1, is characterized in that, described screening out the second salesman set that described real-time location information matches with described reservation address information from described first salesperson set, comprising: Draw a heat map based on the historical order location information of the target city area; The heat map is divided into grids according to a preset ratio strategy to obtain a plurality of grid regions; Taking the grid area where the reservation address information is located as the center, if the real-time location information is within 8 grid areas surrounding the center, the real-time location information matches the reservation address information, wherein, The grid area in the center and the 8 grid areas around the center are distributed in a nine-square grid. 5. method according to claim 1, is characterized in that, described screening out the second salesman set that described real-time location information matches with described reservation address information from described first salesperson set, comprising: If the path distance between the real-time location information and the reservation address information is less than or equal to a preset distance, the real-time location information matches the reservation address information. 6. The method according to claim 1, wherein the prioritization is carried out to all the salespersons in the second salesperson set based on preset rules, comprising, Regularly acquire all business data within the most recent preset time range, input the acquired business data into the preset data statistical analysis system for statistical analysis, and obtain the value of each preset performance index of each salesperson through statistical analysis; Calculate the value of each preset performance index of each salesperson according to the preset scoring calculation rules, and calculate the total performance score of each salesperson; Prioritize each salesperson in descending order of their total performance points. 7. An order distribution platform, characterized in that, comprising: a receiving module, configured to receive order information uploaded by the user through the terminal, where the order information includes user level and reservation address information; The first screening module is used to obtain the level information of all salesmen, and filter out the first salesperson set whose level information matches the user level; The second screening module is configured to obtain the real-time location information of each salesperson in the first salesperson set, and filter out the second salesperson whose real-time location information matches the reservation address information from the first salesperson set gather; A priority sorting module, used for prioritizing all salespersons in the second salesperson set based on preset rules; The allocation module is used for allocating the order information to the task list of the target salesperson, wherein the target salesperson is the salesperson with the highest priority. 8. An order distribution platform comprising at least one processor; and, a memory communicatively coupled to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to execute the at least one processor of any of claims 1-6 Order allocation method. 9. An order distribution system, characterized in that the order distribution system comprises several clients, servers, and an order distribution platform as claimed in claim 8; the several clients and servers all communicate with the platform connect. 10. A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented .

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